{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "33b6cb23",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import json\n",
    "import os\n",
    "import math\n",
    "from core.data_processor import DataLoader\n",
    "from core.model import Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "16e2624e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 这两行代码解决 plt 中文显示的问题\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']\n",
    "plt.rcParams['axes.unicode_minus'] = False"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6cd9d01f",
   "metadata": {},
   "source": [
    "# 显示结果图表函数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "96bb1265",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_results(predicted_data, true_data):\n",
    "    fig = plt.figure(facecolor='white')\n",
    "    ax = fig.add_subplot(111)\n",
    "    ax.plot(true_data, label='正确值')\n",
    "    plt.plot(predicted_data, label='预测值')\n",
    "    plt.legend()\n",
    "    plt.show()\n",
    "\n",
    "\n",
    "def plot_results_multiple(predicted_data, true_data, prediction_len):\n",
    "    fig = plt.figure(facecolor='white')\n",
    "    ax = fig.add_subplot(111)\n",
    "    ax.plot(true_data, label='正确值')\n",
    "    # 填充预测列表，将其在图表中移动到正确的开始位置\n",
    "    for i, data in enumerate(predicted_data):\n",
    "        padding = [None for _ in range(i * prediction_len)]\n",
    "        plt.plot(padding + data, label='预测值')\n",
    "        plt.legend()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c5650676",
   "metadata": {},
   "source": [
    "# 加载实验一的配置文件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "37eb2700",
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "configs = json.load(open('test_2/config.json', 'r'))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "10eac442",
   "metadata": {},
   "source": [
    "# 数据加载器\n",
    "### 创建一个 DataLoader的类 class 来加载数据，为数据加载层提供概括信息\n",
    "* 传入文件名\n",
    "* 确定用于训练与测试的数据百分比的分割变量\n",
    "* 选择一列或多列数据来进行单维或多维分析的列变量"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "fbbfbc69",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = DataLoader(\n",
    "    filename=os.path.join('data', configs['data']['filename']),\n",
    "    split=configs['data']['train_test_split'],\n",
    "    cols=configs['data']['columns']\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ab8f170e",
   "metadata": {},
   "source": [
    "## 1.划分训练集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b214ff1b",
   "metadata": {},
   "outputs": [],
   "source": [
    "x, y = data.get_train_data(\n",
    "    seq_len=configs['data']['sequence_length'],\n",
    "    normalise=configs['data']['normalise']\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7ec373c0",
   "metadata": {},
   "source": [
    "## 2.划分测试集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3467aba5",
   "metadata": {},
   "outputs": [],
   "source": [
    "x_test, y_test = data.get_test_data(\n",
    "    seq_len=configs['data']['sequence_length'],\n",
    "    normalise=configs['data']['normalise']\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "70fa9a26",
   "metadata": {},
   "source": [
    "## 3.模型构建\n",
    "代码框架使用Model类和config.json文件来轻松构建模型的实例\n",
    "构建网络的主函数是build_model（）函数，它接收解析的配置文件。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "c5190211",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Model] Model Compiled\n",
      "Time taken: 0:00:01.176060\n"
     ]
    }
   ],
   "source": [
    "model = Model()\n",
    "model.build_model(configs)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d172c96",
   "metadata": {},
   "source": [
    "# 模型训练\n",
    "我们创建了一个单独的运行模块，它将Model和DataLoader 抽象出来的信息组合起来并用于训练、输出和可视化。"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "502b6c7e",
   "metadata": {},
   "source": [
    "### 一个重要的改变：\n",
    "#### 不使用framework中的 model.train()方法，而使用创建的model.train_generator()  方法\n",
    "#### 训练大型数据集时很容易耗尽内存，当model.train（）函数将整个数据集加载到内存中，\n",
    "#### 然后对内存中的每个窗口标准化时，容易导致内存溢出。\n",
    "~~~\n",
    "~~~\n",
    "#### 使用了Keras的fit_generator（）函数，允许使用python生成器动态训练数据集来绘制数据，这意味着内存利用率将大大降低。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "955b6240",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Model] Training Started\n",
      "[Model] 2 epochs, 32 batch size, 116 batches per epoch\n",
      "Epoch 1/2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Administrator\\Desktop\\lstm-neurons\\core\\model.py:78: UserWarning: `Model.fit_generator` is deprecated and will be removed in a future version. Please use `Model.fit`, which supports generators.\n",
      "  self.model.fit_generator(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "116/116 [==============================] - 31s 208ms/step - loss: 0.0357\n",
      "Epoch 2/2\n",
      "116/116 [==============================] - 23s 202ms/step - loss: 0.0165\n",
      "[Model] Training Completed. Model saved as saved_models\\28112021-174353-e2.h5\n",
      "Time taken: 0:01:28.148865\n"
     ]
    }
   ],
   "source": [
    "# 记忆外生成训练\n",
    "steps_per_epoch = math.ceil((data.len_train - configs['data']['sequence_length']) / configs['training']['batch_size'])\n",
    "model.train_generator(\n",
    "    data_gen=data.generate_train_batch(\n",
    "        seq_len=configs['data']['sequence_length'],\n",
    "        batch_size=configs['training']['batch_size'],\n",
    "        normalise=configs['data']['normalise']\n",
    "    ),\n",
    "    epochs=configs['training']['epochs'],\n",
    "    batch_size=configs['training']['batch_size'],\n",
    "    save_dir=configs['model']['save_dir'],\n",
    "    steps_per_epoch=steps_per_epoch\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef663ad5",
   "metadata": {},
   "source": [
    "# 预测数据\n",
    "\n",
    "* 第一种将以逐点方式进行预测，即我们每次仅预测单个点，将此点绘制为预测，然后沿着下一个窗口进行预测,并再次使用完整的测试数据预测下一个点。\n",
    "* 对完整的序列进行预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "35b2867a",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[Model] Predicting Sequences Multiple...\n",
      "[Model] Predicting Sequences Full...\n",
      "[Model] Predicting Point-by-Point...\n"
     ]
    }
   ],
   "source": [
    "predictions_multiseq = model.predict_sequences_multiple(x_test, configs['data']['sequence_length'], configs['data']['sequence_length'])\n",
    "predictions_fullseq = model.predict_sequence_full(x_test, configs['data']['sequence_length'])\n",
    "predictions_pointbypoint = model.predict_point_by_point(x_test)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "70112d03",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_results_multiple(predictions_multiseq, y_test, configs['data']['sequence_length'])\n",
    "plot_results(predictions_fullseq, y_test)\n",
    "plot_results(predictions_pointbypoint, y_test)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "deep",
   "language": "python",
   "name": "deep"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
